Comparison of Performance of Indian Aviation Service Providers Using Multi-Criteria Decision Models

Asian Journal of Pure and Applied Mathematics

1(1): 16-26, 2019; Article no.AJPAM.138

Comparison of Performance of Indian Aviation Service Providers Using Multi-criteria Decision Models

Mihir Dash1*

1Department of Quantitative Methods, School of Business, Alliance University, Chikkahagade Cross, Anekal Road, Anekal, Bangalore-562106, India.

Author’s contribution

The sole author designed, analysed, interpreted and prepared the manuscript.

Received: 13 June 2019 Accepted: 14 September 2019 Original Research Article Published: 19 September 2019 ______

Abstract

The objective of this study is to compare the performance of players in the Indian aviation industry. The performance indicators for aviation service providers considered in the study include market share, operational efficiency, punctuality, reliability, and customer satisfaction. The study uses the multi-criteria decision models Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) to benchmark performance in the Indian aviation industry. The sample selected for the study comprise the top seven aviation service providers, viz. Indigo Airlines, Jet Airways, Air India, Spice Jet, Go Air, Air Asia, and Vistara. The results of the analysis would enable the aviation service providers to identify their strengths and weaknesses, and take appropriate steps to improve their performance.

Keywords: Indian aviation industry; performance; multi-criteria TOPSIS and AHP.

1 Introduction

The Indian aviation industry is classified into three main segments; namely, scheduled air transport services, i.e. services between two or more places operating according to a published timetable (including domestic and international airlines); non-scheduled air transport services, i.e. chartered flights, where the operator is not permitted to publish a timetable or to issue tickets to passengers; and air cargo services, i.e. air transportation of cargo and mail within India, either on a scheduled or non-scheduled basis. The industry is further subdivided into public players and private players.

The evolution of the ‘modern’ Indian aviation industry started in the late 1990s, with a rapid and dramatic transformation due to the open-sky policy adopted by the Indian government under Liberalisation. Subsequently, with the entry of private players, Indian Airlines, the dominant player at the time, gradually lost its market share to the private airlines. The Indian aviation industry today is dominated by private airlines such as Indigo, Jet Airways, Spice Jet, and Go Air.

______*Corresponding author: E-mail: [email protected], [email protected];

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

Domestic flights are the largest segment of the airlines industry in India, accounting for 76.9% of the industry's total volume; the international flights segment accounts for the remaining 23.1% of the industry. Further, airlines are classified as low-cost carriers and full-service carriers. Low-cost carriers, also known as discount airlines or low-cost airlines, are airlines that offer lower fares in exchange for fewer passenger comforts. Low-cost carriers have had a great impact on the aviation industry [1]. The deep market penetration of low-cost airlines caused conventional carriers to cut flights, close hubs and even abandon service to some cities. Some of the low-cost carriers in the Indian aviation industry include Indigo, Spice Jet, and Go Air. Full-service carriers, on the other hand, provide a wide range of additional comforts, such as entertainment, food, drinks, and so on. There is room for growth in the full-service carrier segment as increasing prosperity leads to demand for quality in-flight services. Some of the full-service carriers in the Indian aviation industry include Jet Airways, Air India, and so on. Some of the new entrants in the industry include Air Asia, Vistara, and Air Costa. As of Dec’ 2015, the top seven players in the Indian aviation industry were: Indigo Airlines (36.7%), Jet Airways (22.5%), Air India (16.5%), Spice Jet (11.6%), Go Air (8.6%), Air Asia (1.7%), and Vistara (1.3%). The seven-firm concentration index was 98.8%, and the HHI = 0.2335; thus, the market can be considered to be moderately concentrated, i.e. a small number of players dominate the market.

1.1 Macro-environmental factors

The Indian aviation industry is one of the fastest growing aviation industries in the world, with a passenger revenue growth of 20.5%, followed by China (12.1%) and Russian Federation (8.8%). Some of the driving factors for the growth and expansion of the Indian aviation industry include the low-cost carriers, modern airports, foreign direct investments in domestic airlines, information technology interventions, and a growing emphasis on regional connectivity. Currently, the Indian civil aviation industry is amongst the top ten in the world, with a market size of around US$16 billion. India has a vision of becoming the third largest aviation market by 2020, and the largest by 2030.

The airline industry operates in a highly regulated political environment favouring passengers over the interest of the airlines. This is because passenger safety is paramount, and political establishments have made strict regulations to prevent safety issues and terrorist hijacking. In recent years lawsuits have increased against airline companies from customers as well as workers.

International airlines are seriously affected by economic and political relations between countries. If there is high tension and an unstable relationship with other countries, then the air traffic falls due to safety concerns of passengers (e.g. between India and Pakistan). The incidence of terrorist attacks generally adversely impacts air travel; e.g. the 9/11 World Trade Centre bombing and the bomb attacks at several key European airports. Another factor is the spread of infectious diseases such as ebola, SARS (Severe Acute Respiratory Syndrome), and MERS (Middle East Respiratory Syndrome). Further, events such as the recent disappearance of Malaysian airline flight MH370 also tend to adversely affect the global airline industry.

Another political factor faced by airline companies is corruption. Getting the requisite permits and licenses involves the payment of bribes, and there is high intervention by the government in this aspect. In fact, the public airlines suffer the most from governmental interference, as they have to make special considerations with respect to selection of routes, free seats to ministers, and so on, which private airlines are not obliged to do. The public airlines are also subject to old labour regulations causing strong labour unions, affecting their flexibility in decision making and quality of service.

The government has taken up many initiatives for the aviation industry. The FDI norms have been relaxed to 74% to further stimulate foreign investment in the industry. FDI inflows in air transport stood at US$ 542.55 million during the period 04/2000 - 11/2014. The Airport Authority of India (AAI) is undertaking to develop an estimated number of about 500 airports that would be required by 2020, in collaboration with state governments and private parties through different Private-Public-Partnership models, with substantial state support in terms of concessional land allotment, financing, tax holidays and other incentives. The government has also taken several steps to encourage foreign tourists, including renewing ties with several

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

countries and enabling visa on arrival by digitising the visa process. In the longer term, the government is taking steps to privatise the public airline Air India by forming a committee comprising bankers, aviation experts and technocrats.

The aviation industry is highly sensitive to several economic factors. Airlines have to cope with declining passengers, high fuel prices, competition from low-cost airliners, labour demands and soaring operating and maintenance costs. Also, air travel is a highly seasonal business, and is severely impacted by business cycles. During boom periods, there is an increase in the demand of flight travel, so prices tend to rise. However, during recession the demand for flights decreases, forcing airliners to reduce prices to attract customers. This reduction in prices and increasing costs such as operating and maintenance costs, insurance costs, fluctuation in fuel prices, and so on will have negative impact on airline industry. During recession many of the airlines might end up bankrupt or suffer heavy loss if they are not able to manage their costs. Airliners are yet to fully recover from the global financial crisis of 2008-09 and the subsequent global slowdown.

There has been a shift in the profile of the passengers travelling in airlines. Due to the reduction in air fares with the entry of low-cost carriers and the increase in income, a larger proportion of air travellers are economy passengers, interested in the basic services only. Thus airlines must analyse this shift and deliver basic services at competitive rates. Additional services, such as food and beverage services, may be provided at a premium.

Technology has impacted airline business positively. With the help of internet, many of the airline companies are now providing internet-based services such as online ticket booking, updated flight information, handling customer complaints, and so on. Further, advances in technology have enabled airlines to reduce their operating costs, improve operational efficiency, and provide better service. This is supported by advanced aviation communications, navigation, and air traffic management systems to improve handling of traffic and to meet the expected growth in demand for airline and cargo services for the next decade. Some of the modern technologies used by aviation sector include bio-monitors, remote video monitoring, remote controlled airliners, bar code technology, touchscreen for easy access, self-service kiosks, and information exchange via mobile.

1.2 Competitive analysis (Porter’s five force model)

Porter identified five competitive forces that shape every industry and every market, determining the intensity of competition and hence the profitability and attractiveness of an industry. The objective of corporate strategy should be to modify these competitive forces in a way that improves the position of the organisation.

The threat of new entrants in the industry is low. There are high entry and exit barriers, as there is a very large capital requirement, requirement of aviation expertise, and a relatively long break-even period. Moreover, the airline industry leverages the efficiencies and the synergies from economies of scale.

The bargaining power of suppliers in the airline industry is very high because of the fact that the external environment affects all the four inputs that airlines have: fuel, labour, aircraft, and airports. For instance, the price of aviation fuel is subject to fluctuations in the global market for oil, which may be due to geo-political and other factors. To reduce costs from fluctuating market prices of fuel airline companies hedge fuel. Similarly, labour is subject to the power of the unions who often bargain and get unreasonable and costly concessions from the airlines. The airline industry needs aircraft either by purchase or on lease basis, which means that the airlines have to depend on two companies, Airbus, and Boeing, for their aircraft needs. Finally, Indian airports are managed by the Airports Authority of India, a single supplier.

The bargaining power of buyers is also high. With the advent of online ticketing and distribution systems, customers no longer have to depend on the agents, intermediaries, or the airlines themselves for their

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

ticketing needs. Thus, customers face very low searching and switching costs. Also, there is not much product differentiation, with all players providing similar services.

The threat of substitutes is low to moderate. For the international carriers, there is low threat of substitutes as customers might not have many choices of other means of transport; but for regional airlines, the threat of substitutes is relatively high, as customers can switch to other means of transport such as car, bus, train, or boat to reach the destination. The major switching costs are time and cost, so for shorter distances customers might be induced by low prices of other means of transport. For business class passengers, improved communication facilities such as video-conferencing have reduced the need to travel for meetings; thus the threat of substitutes is moderate.

Competitive rivalry is very high in the Indian aviation industry, due to the entry of low cost carriers and the high operating costs. Also, the industry is regulated more on the supply side than the demand side, so that airlines are not free to choose which markets to operate and which segments to target. The various airlines are competing for the same customers; they are competing in terms of price, technology, in-flight entertainment, customer service, and so on.

Several different pricing strategies are used by airline operators includes demand-based pricing, season- based pricing, competitive pricing, and value-based pricing. Demand-based pricing or dynamic pricing is used in the short-run, usually within one month before the flight, wherein the fare increases with demand. Season-based pricing recognises the seasonality of the demand, and adjusts fares accordingly; e.g. air fares shoot up to three or four times the basic fare in Deepavali. Competition-based pricing focuses on the fares charged by competitors; if one airlines cuts prices, other airlines are forced to follow in order to compete in the market. Value-based pricing is used to charge a premium based on perceived value to the customer. Also, airlines quite often provide discount or cut fares to frequently communicate to the customers. Penetration pricing is also often used, wherein new services are introduced at low fares.

2 Methodology

The objective of the study is to compare the performance of players in the Indian aviation industry. The performance indicators for aviation service providers considered in the study include market share, operational efficiency, punctuality, reliability, and customer satisfaction [2].

The market share reflects the brand value of the airline, the customers’ willingness to purchase the service. This is the outcome of the airline’s efforts to provide service to match the customers’ requirements. A successful brand will be able to maintain and improve its market share over time. The market share is measured by considering the total number of passengers carried by the service providers (x1).

The passenger load factor measures the occupancy rate, i.e. the average number of seats the airline can fill on its flights. This partially reflects the airline’s operational efficiency, viz. its capacity utilisation. A related indicator is the weight load factor, which also partially reflects the airline’s operational efficiency. For the study, however, only the passenger load factor (x2) has been considered as a measure of operational efficiency.

Punctuality is an important indicator from the point of view of customer expectations. Indigo has built its brand on being on-time. The on-time performance (x3) data available from the DGCA pertains only to four airports: Delhi, Mumbai, Bangalore, and Hyderabad. This has been taken as a measure of punctuality for the study.

Reliability is an important service quality indicator, reflecting whether the service provider is able to perform or deliver the promised service dependably and accurately. The most serious service failure in the case of an aviation service is cancellation of flights. The measure for reliability considered in the study is the percentage of cancellations (x4).

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

Customer satisfaction is perhaps the most important indicator of airline performance. There are several techniques for measuring customer service, including the commonly-used CSAT score, computed by surveying customers. For the study, however, the number of complaints per 10,000 passengers (x5) is considered as the measure for customer (dis-) satisfaction.

The study uses the multi-criteria decision models Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) to benchmark performance in the Indian aviation industry. The sample selected for the study comprise the top seven aviation service providers, viz. Indigo Airlines, Jet Airways, Air India, Spice Jet, Go Air, Air Asia, and Vistara. The data for the study pertained to the years 2015 and 2016 and was collected from the Directorate General of Civil Aviation (DGCA) website1 [3,4,5].

The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision method, based on relative distance to the ideal solution, the point with the best values for all criteria, and the anti-ideal solution, the point with the worst values for all criteria [6,7].

th th The TOPSIS scores are calculated as follows. Let xij denote the value of the j criterion for the i alternative th and wj denote the weight for the j criterion. These values are first normalised so that their sum of squares is unity by taking

= ∑

∗ The ideal point is defined as the point with best values for each of the criteria, and the anti-ideal point ∗ is defined as the point with the worst values for each of the criteria. The distance from each point to the ideal point and anti-ideal point are calculated respectively as follows:

∗ ∗ = ∑ − and ∗ = ∑ − ∗

The TOPSIS score is then calculated as

∗ = ∗ ∗ +

The TOPSIS score Ti indicates how close each alternative is to the ideal and anti-ideal points. The closer the TOPSIS score is to zero, the closer the alternative is to the anti-ideal point, while the closer the TOPSIS score is to one, the closer the alternative is to the ideal point.

The Analytic Hierarchy Process (AHP) is a technique that is used to structure multi-criteria decisions, allowing both quantitative and qualitative comparisons between alternatives. It is particularly applied in group decision making, and a wide variety of decision situations, including choice, i.e. the selection of one alternative from a given set of alternatives, usually where there are multiple decision criteria involved; ranking, i.e. putting a set of alternatives in order from most to least desirable; prioritization, i.e. determining the relative merit of members of a set of alternatives, as opposed to selecting a single one or merely ranking them; resource allocation, i.e. apportioning resources among a set of alternatives; benchmarking, i.e. comparing the processes in one's own organization with those of other best-of-breed organizations; quality management, i.e. dealing with the multidimensional aspects of quality and quality improvement; and conflict resolution, i.e. settling disputes between parties with apparently incompatible goals or positions.

AHP has four basic steps. The first step is to define the problem and state the goal or objective, define the criteria or factors that influence the goal, and identify the alternatives to be evaluated with respect to the

1 http://dgca.nic.in/reports/Traffic-ind.htm

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

criteria. The second step is to construct the paired comparison matrix between the criteria, using which the weights for each of the criteria are calculated. The third step is to construct the paired comparison matrices for the alternatives for each criterion, using which the ratings for each alternative under each criterion are calculated. The fourth and final step is to synthesize the ratings of each alternative by taking weighted averages, and to select the alternative with highest composite rating [8,9,10].

The scale used for the paired comparison matrix for criteria is an importance scale, ranging from 1 to 9, where ‘1’ represents equal importance, ‘2’ represents equal to moderately more important, ‘3’ represents moderately more important, ‘4’ represents moderately to strongly more important, ‘5’ represents strongly more important, ‘6’ represents strongly to very strongly more important, ‘7’ represents very strongly more important, ‘8’ represents very strongly to extremely more important, and ‘9’ represents extremely more important. The scale used for the paired comparison matrix for alternatives under each criterion is a preference scale, ranging from 1 to 9, where ‘1’ represents equally preferred, ‘2’ represents equally to moderately more preferred, ‘3’ represents moderately more preferred, ‘4’ represents moderately to strongly more preferred, ‘5’ represents strongly more preferred, ‘6’ represents strongly to very strongly more preferred, ‘7’ represents very strongly more preferred, ‘8’ represents very strongly to extremely more preferred, and ‘9’ represents extremely more preferred.

The AHP scores are computed as follows. Let the paired comparison matrix for the criteria be given by ((cij)), with diagonal entries cii = 1. The matrix is normalized so that the column totals are equal to unity by taking

̃ = ∑

The priority/weight for each criterion is then obtained by taking averages of the normalized values, viz.

1 = ̃

To test the consistency of the paired comparisons for the criteria, the priorities are multiplied into each row of the paired comparison matrix

Each of these weighted averages is then divided by the corresponding priority/weight

= ⁄

The eigenvalue is obtained by averaging the vi’s

1 =

The consistency index is obtained as

− = − 1

Finally, the consistency ratio is

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= ⁄ where RIn is the random index, given in the table below (Saaty, 1980).

n 3 4 5 6 7 8 RIn 0.58 0.90 1.12 1.24 1.32 1.41

The pairwise comparisons are considered to be reasonably consistent if the consistency ratio is less than 0.1 [11].

k Similarly, let ((cij )) represent the paired comparison matrix for the alternatives under the kth criterion. Normalizing,

̃ = ∑

The weight for each alternative under each criterion is then obtained as

1 = ̃

The final AHP score for each alternative is obtained by taking a weighted average of the alternative weights with the criteria weights

By construction, the AHP scores are non-negative values summing to unity. An alternative with a higher AHP score is preferred over one with a lower AHP score. The alternatives may be ranked accordingly.

3 Analysis

The basic data of the performance indicators used for the study is presented in Table 1a and Table 1b below.

Table 1a. Performance indicators for the sample aviation service providers for 2015

Passengers Passenger load On-time Cancellations Complaints per (in lakhs) factor performance 10,000 pax Indigo Airlines 297.43 83.7 83.80% 0.38% 0.73 Jet Airways 182.24 81.7 79.98% 0.86% 1.40 Air India 133.35 79.8 73.38% 1.45% 2.06 Spice Jet 94.25 89.8 73.05% 0.92% 2.26 Go Air 69.28 82.6 78.23% 0.65% 2.10 Air Asia 13.93 77.7 85.02% 0.57% 1.22 Vistara 10.66 63.1 94.33% 0.52% 0.28

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Table 2b. Performance indicators for the sample aviation service providers for 2016

Passengers Passenger load On-time Cancellations Complaints (in lakhs) factor performance per 10,000 pax Indigo Airlines 392.68 84.9 80.26% 0.70% 0.34 Jet Airways 189.98 79.8 77.71% 0.63% 1.42 Air India 146.26 79.0 72.38% 1.07% 2.38 Spice Jet 126.84 92.7 80.64% 0.44% 0.64 Go Air 81.90 87.2 74.26% 0.37% 1.02 Vistara 25.16 75.5 83.44% 0.22% 0.16 Air Asia 23.94 84.6 79.28% 1.11% 0.70

Indigo Airlines was found to dominate in both years in terms of market share (36.7% and 39.3%, respectively), with Jet Airways and Air India following in second and third place. The new entrants Air Asia and Vistara were found to have experienced a growth in market share (1.7% to 2.4% for Air Asia and 1.3% to 2.5% for Vistara).

In terms of passenger load factor, however, Spice Jet was the most efficient airline, followed by Indigo Airlines and Go Air; in fact, Go Air overtook Indigo in this respect in 2016. The least efficient airline was Vistara, followed by Air India.

In terms of on-time performance, the new entrants Vistara and Air Asia surpassed the industry leader Indigo Airlines in 2015; however, by 2016 Air Asia was unable to sustain its performance, dropping to almost the bottom. Air India and Spice Jet were the worst performers in this indicator.

In terms of reliability, Indigo Airlines was at the top in 2015, but it lost its edge to the new entrant Vistara slipping to fifth position in 2016. Air India was the worst performer in this indicator in 2015, while the new entrant Air Asia slipped to the bottom in 2016.

In terms of customer satisfaction, the new entrant Vistara was found to be the best performer, followed by Indigo Airlines, in both years. Spice Jet was the worst performer in this indicator in 2015, but it dramatically improved in 2016; Air India was the worst performer in 2016.

The pairwise comparison matrix for the performance indicators is presented in Table 2 below.

Table 2. Pairwise comparison of performance indicators

x1 x2 x3 x4 x5 x1 1 1/2 1/3 1/5 1/7 x2 2 1 1/2 1/3 1/5 x3 3 2 1 1/2 1/3 x4 5 3 2 1 1/2 x5 7 5 3 2 1

The consistency ratio was found to be CR = 0.06806, indicating satisfactory consistency for the pairwise comparisons. The resultant weights for the performance indicators are presented in Table 3 below.

Table 3. Weights for the performance indicators

Weight Passengers (in lakhs) 0.058692 Passenger load factor 0.088628 On-time performance 0.152019 Cancellations 0.260218 Complaints per 10,000 pax 0.440443

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The most important performance indicator was customer satisfaction, followed by reliability and punctuality. Thus, the customer service indicators are attributed much greater weightage than the market share and operational efficiency indicators. This reflects the importance of customer service in sustaining airlines’ competitive advantage.

These resultant weights were used for both the AHP analysis and the TOPSIS analysis.

The TOPSIS scores for the aviation service providers are presented in Table 4 below.

Table 4. TOPSIS scores for the aviation service providers

2015 2016 Indigo Airlines 0.965425 0.928331 Jet Airways 0.499040 0.408211 Air India 0.045902 0.013150 Spice Jet 0.128541 0.845356 Go Air 0.258201 0.675592 Air Asia 0.556656 0.551592 Vistara 0.810218 0.891012

According to the TOPSIS scores, Indigo Airlines was found to be the best performer, followed by Vistara, and Air India was found to be the worst performer, in both years. Spice Jet was found to have dramatically improved its performance in 2016, rising to the third position. Go Air was also found to have improved its performance, entering into the forth position. Jet Airways, which is a large player in terms of their market share (22.5% in 2015 and 19.0% in 2016), was found to underperform due to its weak performance on customer service indicators.

The AHP scores for the aviation service providers are presented in Table 5a and 5b below.

Table 5a. AHP scores for the aviation service providers for 2015

Passengers Passenger On-time Cancellations Complaints AHP (in lakhs) load factor performance per 10,000 score pax Indigo Airlines 0.464494 0.168069 0.146009 0.329243 0.244127 0.257553 Jet Airways 0.202536 0.125907 0.086239 0.071954 0.103022 0.100255 Air India 0.124873 0.091476 0.032138 0.021385 0.039911 0.043465 Spice Jet 0.082433 0.381817 0.030556 0.060098 0.027982 0.071286 Go Air 0.061341 0.145245 0.065448 0.133309 0.036908 0.077368 Air Asia 0.032894 0.066702 0.177020 0.174749 0.132108 0.138411 Vistara 0.031429 0.020785 0.462590 0.209262 0.415942 0.311662

Table 5b. AHP scores for the aviation service providers for 2016

Passengers Passenger On-time Cancellations Complaints AHP (in lakhs) load factor performance per 10,000 score pax Indigo Airlines 0.499987 0.128545 0.163669 0.078393 0.199830 0.174032 Jet Airways 0.165320 0.051053 0.080925 0.097932 0.051093 0.074517 Air India 0.111657 0.045165 0.023850 0.028463 0.020645 0.030682 Spice Jet 0.092783 0.428264 0.187440 0.177088 0.151463 0.184689 Go Air 0.060728 0.196094 0.036726 0.225934 0.123294 0.139623 Air Asia 0.034633 0.124448 0.121774 0.024696 0.137445 0.098537 Vistara 0.034893 0.026430 0.385615 0.367493 0.316230 0.297921

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According to the AHP scores, Vistara was found to be the best performer and Air India was found to be the worst performer, in both years. Indigo Airlines was found to be in the second position in 2015, but it slipped to third position in 2016, perhaps due to the decrease in its on-time performance and the increase in cancellations. As before, Spice Jet was found to have dramatically improved its performance in 2016, rising to the second position; Go Air was also found to have improved its performance.

4 Conclusion

The results of the TOPSIS and AHP analyses were found to be contradictory. According to the TOPSIS scores, Indigo Airlines is the best performer, whereas according to the AHP scores, Vistara is the best performer. Both methodologies were found to be adequately sensitive; in particular, Spice Jet and Go Air were found to have improved their performance under both TOPSIS and AHP analyses. However, it is not clear which of these methodologies is more appropriate.

The results of the study reflect the dynamism of the aviation industry. The full-service carriers Jet Airways and Air India have been facing a challenge from the low-cost carriers Indigo Airlines, Spice Jet, and Go Air. The new entrants, particularly Vistara, are posing a further challenge to the market leaders Indigo Airlines, Jet Airways, and Air India. In particular, the worst performer, Air India, is in a serious condition, on the verge of being privatized. The results of the study thus reflect the competitive forces in the industry, with customer service increasingly becoming the critical factor. Thus, the industry leader Indigo Airlines must improve its customer service performance in order to remain at the top.

The contradictory nature of the results of the study could be due to the higher weightage given to customer service indicators. Clearly, if higher weightage is given to market share and/or operational efficiency, Indigo Airlines would be the best performer. On the other hand, the better levels of customer service shown by Vistara may be because it is a new entrant, with a relatively smaller scale of operations. Thus, a more careful analysis of the impact of Vistara’s entry into the industry may give better insight.

There are several limitations inherent in the study. The sample size for the study was very small, considering only seven aviation service providers for just two years. This limitation arose due to the unavailability of data for a longer period. Also, the study only considered a small set of performance indicators, such as operational costs and profitability. [2] provides many possible performance indicators that can be used. Another aspect of airline performance that should be examined in more detail is that of technical efficiency. The non-parametric Data Envelopment Analysis may be applied for this purpose.

Competing Interests

Author has declared that no competing interests exist.

References

[1] Sabre. The evolution of the airline business model; 2010. Available:http://www.sabreairlinesolutions.com/images/uploads/Hybrid_Model_Brochure.pdf

[2] Fry J, Francis G, Humphreys I. An international survey of performance measurement and benchmarking by airlines. Working Paper, Accounting and Finance Research Unit, Open University Business School; 2004.

[3] Directorate General of Civil Aviation, Handbook on Civil Aviation Statistics 2014-15, New Delhi: Directorate General of Civil Aviation; 2015.

Dash; AJPAM, 1(1): 16-26, 2019; Article no.AJPAM.138

[4] Directorate General of Civil Aviation, Handbook on Civil Aviation Statistics 2015-16, New Delhi: Directorate General of Civil Aviation; 2016.

[5] Directorate General of Civil Aviation, Handbook on Civil Aviation Statistics 2016-17, New Delhi: Directorate General of Civil Aviation; 2017.

[6] Hwang CL, Lai YJ, Liu TY. A new approach for multiple objective decision making. Computers and Operational Research. 1993;20:889-899.

[7] Hwang CL, Yoon K. Multiple attribute decision making: Methods and applications. New York: Springer-Verlag; 1981.

[8] Saaty TL. The analytic hierarchy process, New York: McGraw Hill; 1980.

[9] Saaty TL. Relative measurement and its generalisation in decision making: Why pairwise comparisons are central in mathematics for the measurement of intangible factors - The analytic hierarchy/network process. Review of the Royal Academy of Exact, Physical and Natural Sciences, Series A: Mathematics. 2008;102(2):251-318.

[10] Saaty TL, Forman EH. The hierarchon: A dictionary of hierarchies. Pittsburgh, Pennsylvania: RWS Publications; 1992.

[11] Alonso JA, Lamata MT. Consistency in the analytic hierarchy process: A new approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2006;14(4):445-459. ______© Copyright Global Press Hub. All rights reserved.